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CURL: Contrastive Unsupervised Representations for Reinforcement Learning

Machine Learning Street Talk (MLST)

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Unsupervised vs. Supervised Learning Dynamics

This chapter explores the dynamics between unsupervised and supervised learning, highlighting the advantages of pre-training with unlabeled datasets. It emphasizes how unsupervised methods can extract richer data insights and improve model generalization, particularly in reinforcement learning. The narrative is enriched with personal experiences in the field, showcasing the evolution of understanding and the continual exploration of innovative learning methods.

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